Staff MLOps Engineer - Ingénieur(e) MLOps expert(e) (niveau Staff)

NBCUniversal • Montreal, QC

2d

About The Position

We are seeking a Staff MLOps Engineer with experience building and scaling infrastructure for large 2D and 3D media datasets. In this role, you will develop and own the backbone of our machine learning lifecycle, ensuring that data pipelines are automated, reproducible, and highly performant at scale. You will work on enabling seamless model training, deployment, and monitoring across complex, multimodal systems, supporting the evolution of cutting-edge AI/ML applications.

Requirements

• Master's degree in Computer Science, Engineering, Mathematics, or a related field
• Minimum of 5+ years of relevant industry experience, ideally within a fast-paced, high-growth tech environment.
• Proven experience as an MLOps Engineer in a fast-paced environment in applied machine learning.
• Prior experience in industries with complex multi-disciplinary teams such as robotics, smart grids, precision agriculture, game development, or aerospace.
• Fluency with Python, Git, and the Unix shell.
• Deep familiarity with Docker, Kubernetes, and workflow orchestrators (e.g., Airflow, Prefect, or Kubeflow)
• Familiarity with collaborative tools such as Jira/Confluence, Slack and a Git server.
• Strong Mathematical Background: Preferred for understanding the resource demands of 3D data transformations.
• Conscientiousness: High attention to detail regarding system reliability and data security.
• Systems Thinking: Ability to translate abstract ML requirements into concrete, scalable cloud or on-prem infrastructure

Nice To Haves

• Strong Mathematical Background

Responsibilities

• Cross-Functional Coordination: Work with partner ML and Annotation engineers and TPMs to spec out infrastructure and training requirements.
• Pipeline Automation: Design and maintain robust CI/CD and CT (Continuous Training) pipelines for complex multimodal models.
• Data Lifecycle Management: Implement versioning and storage strategies for massive 2D/3D datasets to ensure reproducibility and high-throughput access.
• Monitoring & Observability: Deploy and manage systems for monitoring model performance and data drift in production environments.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior